Move DataValidator and RequiredDataValidator documentation to API section

docs/api.rst

@@ -13,6 +13,8 @@ API documentation
    api/datastructureconfig
    api/codelist
    api/regionprocessor
+   api/datavalidator
+   api/requireddatavalidator
    api/countries
    api/nuts
    api/testing

docs/user_guide/validation/data-validation.rst → docs/api/datavalidator.rst

@@ -2,8 +2,8 @@
 
 .. currentmodule:: nomenclature
 
-Data validation
-===============
+**DataValidator**
+=================
 
 **Data validation** checks if timeseries data values are within specified ranges.
 
@@ -67,12 +67,13 @@ tolerance of 1 to the value of 2, with warning level ``error`` by default.
 Standard usage
 --------------
 
-Run the following in a Python script to check that an IAMC dataset has valid data.
-
 .. code-block:: python
 
   from nomenclature.processor import DataValidator
 
   # ...setting directory/file paths and loading dataset
 
   DataValidator.from_file(data_val_yaml).apply(df)
+
+.. autoclass:: DataValidator
+   :members: from_file, from_codelist, apply

docs/api/regionprocessor.rst

@@ -4,4 +4,4 @@
 ===================
 
 .. autoclass:: RegionProcessor
-   :members: from_directory, validate_with_definition, apply, check_region_aggregation
+   :members: from_directory, apply, check_region_aggregation, revert

docs/user_guide/validation/required-data-validation.rst → docs/api/requireddatavalidator.rst

@@ -2,10 +2,10 @@
 
 .. currentmodule:: nomenclature
 
-Required data validation
-========================
+**RequiredDataValidator**
+=========================
 
-**Required data validation** checks if certain models, variables, regions and/or 
+**Required data validation** checks if certain models, variables, regions and/or
 periods of time are covered in the timeseries data.
 
 For this, a configuration file specifies the model(s) and dimension(s) expected
@@ -31,13 +31,14 @@ years 2020, 2030, 2040 and 2050.
 Standard usage
 --------------
 
-Run the following in a Python script to check that an IAMC dataset has valid
-required data.
-
 .. code-block:: python
 
   from nomenclature import RequiredDataValidator
 
   # ...setting directory/file paths and loading dataset
 
   RequiredDataValidator.from_file(req_data_yaml).apply(df)
+
+
+.. autoclass:: RequiredDataValidator
+   :members: from_file, apply, check_required_data_per_model, validate_with_definition

nomenclature/cli.py

@@ -230,8 +230,8 @@ def run_workflow(
     input_file : Path
         Input data file, must be IAMC format, .xlsx or .csv
     workflow_file : Path
-            Path to the workflow file,
-            default: current working directory / "workflow.py"
+        Path to the workflow file,
+        default: current working directory / "workflow.py"
     workflow_function : str
         Name of the workflow function inside the workflow file, default: main
     output_file : Path | None
@@ -252,7 +252,7 @@ def run_workflow(
     if not hasattr(workflow, workflow_function):
         raise ValueError(f"{workflow} does not have a function `{workflow_function}`")
 
-    df = getattr(workflow, workflow_function)(IamDataFrame(input_file))
+    df: IamDataFrame = getattr(workflow, workflow_function)(IamDataFrame(input_file))
     if output_file is not None:
         df.to_excel(output_file)